What are the sleep characteristics of elite female athletes? A systematic review with meta-analysis

With the recent growth in female sport, practitioners need to be able to provide specific support to female athletes to ensure their sleep, health and athletic performance are optimised. Examine the patterns, duration and quality of sleep among elite female athletes, and consider the impact of situational challenges and their effects on the sleep of elite female athletes. Data was located through a search of SPORTDiscus, MEDLINE and Scopus from inception up to May 2021. Studies needed to be peer-reviewed research reporting quantitative sleep outcomes for female athletes ≥ 18 years of age and competing at a predefined elite level. A meta-analysis was performed on habitual sleep outcomes (e.g. total sleep time [TST] and sleep efficiency [SE]) measured with actigraphy. A total of 38 studies were included. Meta-analysis showed habitual TST (n = 14) was 7.8 h [7.4, 8.2] (mean [95% CI]), and SE was 86.7% [84.7, 88.6], with high variability among studies (I2 = 97.8–98.2%). Subjective sleep complaints are common before a competition, as do post-training sleep disturbances (63% studies report TST decrease), and post-competition sleep disturbances (75% studies report TST decrease). Female athletes achieve satisfactory objective sleep quantity and quality during habitual periods, but experience sleep disturbances pre- and post-situational challenges. There is high variability of objective sleep outcomes, demonstrating the individual nature of habitual female athlete sleep. Overall, future research must focus on optimising the sleep appraisal methods and creating high-quality study designs in a broader number of sports.


INTRODUCTION
Sleep is an essential requirement for human health, and an integral component in preparation for, and recovery from, athletic training and competition [1]. Important biological processes occur during sleep, including the restoration of immune and endocrine systems, and integral metabolic processes [2]. However, elite athletes may experience suboptimal habitual sleep patterns [3] (i.e. during at home periods under normal living conditions without situational demands) as well as regularly encountering situational challenges such as competition schedules [4] and travel demands [5] that can lead to additional sleep disturbances.
In the general population, polysomnography (PSG) measures suggest females have longer total sleep time (TST), shorter sleep onset latencies (SOL) and better sleep efficiency (SE) than males [6]. Yet females subjectively report poorer sleep than males, including longer SOL and more nocturnal awakenings [7]. Since aspects of objective sleep appear superior in females, other factors may be influencing their subjective sleep ratings, including the misalignment between circadian rhythms (e.g. core body temperature minimum and pineal What are the sleep characteristics of elite female athletes? A systematic review with meta-analysis international, professional, national or Division I collegiate); (5) the study reported quantitative data on sleep outcomes; and (6) the studies did not report data on sleep outcomes following concussion.
Only English language studies were included.

Data extraction and quality appraisal
Data from the eligible studies were extracted by KHM using a predesigned and piloted data extraction form. Only baseline sleep data was used if a study implemented an intervention. 'Eliteness' was assessed by applying the taxonomy of Swann and colleagues [18], ranking participants on a continuum (score range [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] and allowing categorisations from 'semi-elite', through 'competitive elite', and 'successful elite', to 'world-class elite'. This taxonomy has previously been employed in systematic reviews of elite athlete sleep [3]. KHM and KLP evaluated the quality of the studies using the Newcastle-Ottawa Scale (NOS) adapted for cross-sectional studies [19]. All score disagreements were discussed and if they could not be agreed upon, were resolved by BC. The adapted NOS has previously been used in systematic reviews of elite athlete sleep [3].

Statistical analysis
For studies that reported habitual sleep outcomes (i.e. TST, SE, SOL) measured objectively at night (i.e. not naps), random-effects metaanalyses were performed. To normalise effect sizes, the means of eligible studies were transformed with the measure argument set to MN (i.e. raw mean) [20]. The I 2 statistic was used to assess heterogeneity, with I 2 values of < 25%, 25%-50% and > 50% considered low, moderate and high heterogeneity respectively [21]. Forest plot reference lines were placed at the recommendations of 7 h for TST [22], > 85% for SE [23] and < 20 min for SOL [24]. Metaregression was undertaken to assess if sport, participant number and nights of sleep assessment affected sleep variables (i.e. TST, SE and SOL). The meta-analysis and meta-regression were conducted using the metaphor [20]  For studies assessing habitual sleep using subjective methods, and studies exploring the impact of situational challenges to sleep (i.e. competition, training and travel), results are presented qualitatively. This is due to the lack of common sleep assessment methods, reporting standards and outcome variables.

Included studies and characteristics
The search strategy returned 422 results (Fig 1). After removal of duplicate (n = 105) and irrelevant articles (n = 192), a total of 125 studies were retained for full-text screening. Following eligibility assessment, 87 studies were excluded as they did not meet the inclusion criteria, leaving 38 studies eligible for review.
Sleep was assessed mainly with subjective methods, with eight studies utilising single questions regarding subjective sleep and nine of cortisol following short-term sleep restriction [14], and fewer sleep disturbances after overnight stress [15]. Despite this conflicting evidence, the resulting health impacts of sleep loss in females is more evident with females at an increased risk compared to males for depression and mood disturbance [16] as well as dysfunction of metabolic and cardiovascular processes [17]. Collectively, though current evidence is equivocal, acute or chronically insufficient sleep could have a detrimental effect on the health and athletic performance of female athletes.
With the recent growth in female sport, practitioners need to be able to provide appropriate and specific support to female athletes to ensure their sleep, and thus health and athletic performance are

MATERIALS AND METHODS
The present systematic review with meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and registered with PROSPERO (CRD42017076869).

Eligibility criteria and selection process
The eligibility of the retrieved records was independently assessed by KHM based on title and abstract. If the information was unclear, the full-text article was screened. Duplicate and irrelevant articles were excluded based on abstract and title by KHM. Articles deemed eligible for full-text review were retrieved and screened against the inclusion criteria by KHM and confirmed by KLP.
Studies were required to meet the following inclusion criteria: (1) the study was published as original research in a peer-reviewed journal as full-text article; (2) data was explicitly reported for female athletes; (3) the female athletes were ≥ 18 years of age; (4) the female athletes were competing at an elite level (defined as Olympic, Biology of Sport, Vol. 39 No3, 2022 753 What are the sleep characteristics of elite female athletes? using the Pittsburgh Sleep Quality Index (PSQI) [25]. Another four studies utilised alternative survey methods to assess sleep. Only one study used an athlete specific questionnaire, the Athlete Sleep Screening Questionnaire (AASQ) [26]. Seven studies assessed sleep solely with objective methods, one using PSG and six using wrist actigraphy.
In total, 14 studies used combined objective and subjective assessments of sleep, with 12 using wrist actigraphy and sleep diaries. Two studies implemented PSG in conjunction with subjective sleep quality (one using a visual analogue scale, the other a sleep questionnaire).
In regard to actigraphy analysis methodology, ten applied the default device sleep-wake threshold, four specified using the medium threshold, and three did not comment on the threshold used. No study compared subjective and objective sleep assessments.

Qualitative synthesis
Of the habitual studies, one compared the sleep of female athletes to age and a sex-matched control group using self-report, finding triathletes reported sleeping longer than the control group (10 h vs. 7 h) [27]. As part of a study involving multi-sport athletes, Leeder and colleagues compared the sleep of athletes with an age and sexmatched control group [1]. However, the normative sleep data provided did not distinguish female from male athletes when comparing the athletes with the control group. A recent study also compared the sleep of male and female Australian Rules Football (AFL and AFLW) players [28]. Compared to the AFL players, AFLW had less TST (7.9 ± 0.5 vs 7.1 ± 0.6 h, p = 0.000) and lower SE (89.5 ± 2.8 vs 84.0 ± 4.4 %, p = 0.000). Habitual napping practices were examined in five studies [29][30][31][32][33], finding 23.6-35.8% of athletes nap two or more times per week for 0:30-1:00 h [32,33].
A summary of habitual sleep characteristics assessed using methods other than actigraphy are provided in Table 1.
Subjective sleep quality and self-reported sleep disturbances during normal training and out of competition periods were described

Habitual sleep
Sleep characteristics during normal training or out of competition periods were described in 26 studies.

Quantitative synthesis
The majority of habitual sleep studies (n = 16) were conducted using actigraphy. Of these studies, 15 presented data for one or more variables, and therefore, these studies were able to be used in the meta-analysis. Only eight of the included studies recruited 'competitive elite' athletes. In addition, based on the NOS assessment [19], two of the studies included in the meta-analysis were high quality. study assessed subjective sleep over three consecutive nights (the night before, the night of, and the night following competition) on 15 separate occasions during a competitive netball season [44].
Subjective TST differed (p < 0.05) between both the night before (8:29 ± 0:44 h) and the night following the game (8:09 ± 0:46 h) compared to game night (6:52 ± 0:40 h) [44]. One study used the athlete specific AASQ to determine sleep problems during competition (implemented on the final day of competition period) in a cohort of University Games athletes [29]. The soccer players in this cohort had a mild AASQ 'sleep difficulty score' (5.4 AU [4.2, 6.6]). In addition, approximately 26% of these athletes had moderate to severe sleep problems (i.e. AASQ score between 8-17) during competition.
Two studies used the Competitive Sports, Sleep and Dreams Questionnaire, designed to assess sleep habits and disturbances prior (within 12 months) to important competitions [45,46]. Athletes reported a high prevalence of pre-competition sleep concerns, particularly problems falling asleep (79-83%); waking up early in the morning (29-47%); and nocturnal waking (36-43%) [45,46]. In contrast, Brandt and colleagues observed 63% of Brazilian athletes experienced good to great sleep quality before important competitions when assessed with a single question metric [47].
Ten studies using wrist actigraphy provide the most information about the effects of competition on female athletes' sleep. During an intensive netball tournament, bedtime and wake time were earlier (p = 0.01) and SE greater when compared to normal training (p = 0.03) [30]. In comparison, across two seasons of basketball competition, there was no difference in SE between home compared in 17 studies. Five studies [31][32][33][34][35] used the PSQI to assess sleep quality, with four identifying mean global scores above the threshold indicative of 'poor sleepers' (> 5 AU [32,35] and > 6 AU [33,34]).
PSQI sub-category scores also identified 4.3% of athletes experience long sleep latencies and 18.5% have twitching and jerking legs during sleep [33]. One study used the AASQ, finding that soccer players had none to mild sleep problems (4.4-4.7 AU) one month-pre and one-month post competition [29]. Subjective sleep quality was assessed by eight studies using a single question approach. Although the assessment scales and scoring of these questions varied, results indicate athletes experience 'normal' to 'good' sleep quality over assessment periods ranging from one to twelve days [30,[36][37][38].
Three studies used other questionnaire methods to assess general sleep disturbance, frequently identifying sleep problems such as difficulty falling asleep, nocturnal waking [39,40] and waking up tired [41]. A summary table of habitual sleep quality and sleep disturbance is provided in Table 2.

Effects of competition on sleep
Nine studies used subjective methods to investigate the effect of competition on sleep (Table 3). Two studies (same cohort of participants) reported results of a PSQI assessment pre-competition, with 77.6% of rhythmic gymnasts having a global score > 5 AU (mean score = 7 AU), indicative of poor sleep [41,42]. The gymnasts who had higher performance ranking scores during competition reported worse sleep quality (mean global score = 8 AU) compared to those with lower scores (mean global score = 6 AU) [41]. One

Effects of training on sleep
Studies exploring the influence of training on sleep ( In the three studies specifically comparing evening training and rest days, TST was reduced following evening training compared to a rest day [54][55][56][57]. For example, following evening training, soccer players had significantly less TST (7:09 ± 0:28 h, p < 0.001) compared to the night following a rest day (8:35 ± 0:33 h) [54]. As measured by PSG, swimmers experienced 10% more sleep movements at the to away matches, or for regular compared to doubleheader rounds where two games are played in one round of competition [48]. However, on the night before doubleheaders, TST was approximately one hour greater compared with baseline (p = 0.022) and match-day (p = 0.007) [48]. Across a four-week period encompassing five games (three home, two away), 12 basketball players experienced TST of 8.1 ± 1.6 h, SE of 92.0 ± 5.0% and SOL of 30.0 ± 29.0 min [49].

Effects of travel on sleep
Three studies have investigated the impact of travel on sleep. In a pilot study by Hill and colleagues, subjective sleep was monitored in footballers (n = 7) seven days before, and 12 days following international westward travel [36]. Compared to pre-travel adaptable and individualised 'tool-box' style sleep interventions [60] to be implemented with female athletes. The present review also highlights that female athletes experience post-training, pre-competition and post-competition sleep disturbances and altered sleep-wake patterns.

Habitual sleep
Studies examined in the present review suggest female athletes attain TST within the recommended duration of sleep for adults (7-9 h) [22], albeit at the middle of these recommendations (Fig 2; [23]. Despite the satisfactory objective sleep quality, female athletes consistently report difficulties falling asleep and nocturnal waking [39,40]. Comparable subjective sleep problems are associated with psychosocial distress and high inflammatory biomarkers in general population females [12]. The present findings on habitual sleep suggest female athletes obtain satisfactory sleep quantity and quality. However, there are a number of methodological concerns that may influence the interpretation of the current evidence base and must be improved in future studies for practitioners to provide athletes with effective sleep feedback and recommendations. For example, habitual sleep findings are influenced by a lack of consistency and validity in sleep assessment methods. Activity monitors, such as wrist actigraphy, have emerged as a valid alternative to the gold standard of PSG, especially when working with elite athletes in field-based settings [61]. However, they may underestimate sleep duration and overestimate wake duration depending on the sleep-wake threshold applied [61]. Of the studies that used wrist actigraphy, sleep-wake thresholds were briefly described by the majority of studies as being calculated using the default device threshold (typically the medium threshold) [61]. Considering and reporting the choice of sleep-wake threshold in future studies will yield the best combination of the agreement, sensitivity and specificity for the assessment of sleep.
Seven days to three weeks of wrist actigraphy sleep assessment is also necessary to obtain an accurate pattern of sleep that reflects weekly or social rhythms [62]. However, only Staunton  Sleep disturbances and changes to sleep-wake patterns are evident following double-header rounds of competition [48], evening training [54][55][56], and following competition [50], especially evening competition [38,44,51,52]. In addition, female athletes may have reduced sleep durations compared to both non-athletic controls [50], and male athletes participating in the same sport [28]. In male athletes, research has demonstrated post-competition sleep loss can impair physiological, cognitive and perceptual recovery [67]. However, direct comparisons between these findings and female athletes is limited due to sex differences in the physiological response to sleep loss [11][12][13], exercise and recovery (see review [68]). Although this concept was not explored within the studies presented, females tend to have an earlier timing of circadian rhythms (i.e. daily rhythms of body temperature and melatonin secretion are shifted to the left with an earlier peak [8]) and, as such, tend to prefer going to bed and waking earlier than males. High-intensity evening exercise may further advance circadian rhythms of melatonin by approximately 30 min [69]. Therefore, as a result of evening training and competition, female athletes may be sleeping at a later biological clock time [8] compared with male athletes following a comparable stressor. The potential sleep loss and circadian disruption that may occur following evening training and competition, and how this could impair recovery, need to be further investigated in order to be able to optimise female athletes' athletic performance and health.

Limitations
The present review did not determine publication bias. Therefore, it is possible that the included studies are a biased sample of all the relevant studies (e.g. the study selection doesn't include unpublished data and not all data could be presented in summary tables [70,72,73]), and the mean effects computed for sleep variables reflect this bias. In addition to this primary limitation, the initial screening of titles and abstracts were conducted by one author, and only articles published in English and in peer-reviewed journals were included.  [26,65], only one study in the present review implemented an athlete-specific tool [29]. A greater focus on these population-specific tools in future studies would improve the quality of subjective assessments of elite female athlete sleep.
The limited control of menstrual cycle phase also influences the interpretation of habitual sleep findings. Although the impact on sleep architecture itself is currently unclear, evidence suggests hormonal changes throughout the menstrual cycle and exogenous oral contraceptives may influence sleep [10]. In addition, most experimental studies consider menstrual cycle phase due to the potential impact of hormonal fluctuations on human performance (see review [66]).
Sleep studies in other populations routinely assess exogenous contraceptive use or determine menstrual cycle phase at the time of sleep assessment [66]. Despite this, only one study within this review has sufficiently controlled for menstrual cycle phase [37]. Menstrual cycle phase and exogenous contraceptive use should be considered in future investigations to improve the interpretation of findings and allow tailored support to be provided.

Situational challenges
Based on the evidence presented within this review, subjective sleep complaints appear to be common before competition [42,43,45,46]. Conversely, objective sleep assessments indicate improved precompetition SE [30] and TST [38]. Despite these findings, there are a number of methodological concerns that may influence the interpretation of the evidence base, especially for habitual sleep studies. This includes a lack of consistency and validity in sleep assessment tools, low participant numbers, short duration studies, and limited control of menstrual cycle phase. The present review also demonstrates the failure of studies to report sleep outcomes stratified by sex and compare sleep outcomes to a general population non-athletic cohort. With the growth in female sport, practitioners must be able to provide appropriate and specific sleep support to female athletes. For practitioners to have the knowledge to provide this tailored support, research must focus on optimising the sleep appraisal methods to create high-quality study designs in a broader number of sports.

Funding
No sources of funding were received to assist in the preparation of this review.

Conflicts of interest
Kathleen Miles, Brad Clark, Peter Fowler, Joanna Miller and Kate Pumpa declare they have no conflicts of interest.

Availability of data and material
Data is available upon request.

Code availability
Meta-analysis code is available upon request.

Authors' contributions
KM contributed to the design of the review, the literature search,